Q-omics provides the consensus-scored METTL17 profile across patient tissues and cancer cell-line models. METTL17 expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, METTL17 is differentially expressed in 13, with the highest sampling consensus in BLCA. Additionally, METTL17 RNA expression shows 19,071 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KICH, BLCA, and ACC as cancer lineages where METTL17 shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for METTL17 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes METTL17 survival associations across molecular data types. METTL17 RNA expression shows survival associations in the most cancer types (18), followed by mutation status (9) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible METTL17 RNA expression–survival associations across cancer types. High METTL17 expression shows unfavorable associations in KICH, UVM, LIHC, ACC and KIRC, but favorable associations in SCLC. The KICH Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify KICH as the clearest survival context for METTL17 RNA expression.
This table summarizes METTL17 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for METTL17. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. METTL17 shows higher tumor expression in BLCA, HNSC, LIHC, UCEC, STAD and CHOL. The BLCA box plot shows higher METTL17 RNA expression in tumor versus normal tissue (log2 FC = +0.870, t-test p < 0.001).
This table shows molecular features associated with METTL17 in patient tissues and cancer cell lines. In patient samples, METTL17 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, METTL17 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in BREAST and LARGE_INTESTINE.
